Neutrophil-mediated Activation of Epithelial Protease-Activated Receptors-1 and -2 Regulates Barrier Function and Transepithelial Migration
Bibliographic record
Abstract
Neutrophil (PMN) infiltration and associated release of serine proteases contribute to epithelial injury during active phases of mucosal disorders such as inflammatory bowel disease. Previous studies have demonstrated that PMN contact with basolateral surfaces of intestinal epithelial cells in the presence of a chemoattractant results in disruption of barrier function even without transmigration. Similarly, serine protease-mediated activation of epithelial protease-activated receptors (PARs) has been shown to increase permeability. In this study, we assessed whether transmigrating PMNs can regulate barrier function through epithelial PAR activation. Transepithelial resistance (TER) decreased significantly after PMN contact with basolateral surfaces of T84 monolayers or after incubation with PMN elastase and proteinase-3, but not cathepsin G. Inhibition of PMN serine proteases, but not selective inhibition of elastase or cathepsin G, prevented the fall in TER induced by PMN contact and blocked PMN transepithelial migration. Basolateral, but not apical, PAR-1 and -2 activation with selective agonists also decreased TER. PAR-1 and -2 were localized intracellularly and in close proximity to lateral surfaces beneath tight junctions, and expression was increased in colonic mucosa from individuals with Crohn's disease. Combined, but not individual, transfection with small interfering RNAs targeted against epithelial PAR-1 and -2, prevented the fall in TER induced by PMN contact. Furthermore, basolateral PAR-1 and -2 activation induced phosphorylation of myosin L chain kinase and regulatory myosin L chain. Lastly, epithelial PAR-1 and -2 knockdown decreased the rate of PMN transepithelial migration. These results suggest that protease-mediated epithelial PAR-1 and -2 activation, by migrating PMNs, induces signaling events that increase epithelial permeability thereby facilitates PMN transepithelial migration.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".